Automatic dust suppression control method and system based on environmental data

Abstract

The invention relates to the technical field of environment monitoring and automatic control, in particular to an automatic dust suppression control method and system based on environment data, and the method comprises the steps: obtaining environment initial detection data of a to-be-processed region through an environment information monitoring and conveying module; the wind speed condition of the to-be-processed area is analyzed according to the environment initial detection data, an environment dust concentration correction model is established, and environment target monitoring information of the to-be-processed area is obtained based on the correction model and the environment initial detection data; setting a control instruction reference system in the automatic dust suppression equipment, and obtaining a control reference index analysis result based on the environment target monitoring information and the control instruction reference system; and adjusting and controlling the automatic dust suppression equipment in the to-be-processed area based on the control reference index analysis result and the target monitoring information to realize effective treatment of dust in the to-be-processed area. The system has the whole process of monitoring, correction and decision control, and can realize intelligent and efficient environmental dust control.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring and automatic control, and in particular to an automatic dust suppression control method and system based on environmental data. Background Art

[0002] With the acceleration of industrialization and urbanization, dust pollution is becoming increasingly serious. Dust not only harms human health but also damages the ecological environment. Traditional dust suppression control methods often rely on manual operation or fixed modes, which have certain limitations and shortcomings. Traditional methods cannot dynamically adjust operating parameters according to environmental conditions, and dust suppression is not effective in complex environments. Fixed environmental dust suppression modes can lead to problems such as excessive dust suppression or insufficient control. Traditional methods rely heavily on manual settings and empirical judgment, which cannot achieve reasonable control and timely adjustment of dust suppression equipment, making it difficult to meet the dust control needs of different environments.

[0003] To solve the above problems, it is necessary to optimize the existing environmental dust suppression control methods, which will help to perceive and collect environmental information in real time, dynamically adjust and control dust removal equipment, thereby ensuring the effective operation and reasonable control of system equipment, improving dust control efficiency, reducing operating costs, and reducing environmental pollution risks. Summary of the Invention

[0004] In view of the shortcomings of existing methods and the needs of practical applications, in order to solve the problems of poor environmental adaptability, waste of resources, and lack of intelligence of existing environmental dust suppression methods. On the one hand, the present invention provides an automated dust suppression control method based on environmental data, which includes: using an environmental information monitoring and transmission module to obtain the initial environmental detection data of the area to be processed; analyzing the wind speed of the area to be processed based on the initial environmental detection data, establishing an environmental dust concentration correction model based on the wind speed, and obtaining the environmental target monitoring information of the area to be processed based on the environmental dust concentration correction model and the initial environmental detection data; setting a control instruction reference system in the automated dust suppression equipment, and obtaining the control reference index analysis results of the automated dust suppression equipment based on the environmental target monitoring information and the control instruction reference system; adjusting and controlling the automated dust suppression equipment in the area to be processed based on the control reference index analysis results and the environmental target monitoring information, so as to achieve effective control of dust in the processing area. The present invention can collect data such as environmental wind speed, humidity, dust concentration, etc. in real time, avoid control failure caused by detection lag, and design relevant intelligent models to realize intelligent and efficient dust control, so that the method of the present invention can adapt to different environmental control needs.

[0005] Optionally, analyzing the wind speed conditions in the area to be processed based on the initial environmental detection data includes: establishing an environmental wind speed prediction function for the area to be processed based on air movement characteristics and the initial environmental detection data; analyzing environmental wind speed results corresponding to different times in the area to be processed using the environmental wind speed prediction function; and analyzing the wind speed conditions in the area to be processed based on the environmental wind speed results and the initial environmental detection data. The present invention can be applied to different environmental scenarios, further ensuring that the dust suppression strategy matches the actual environmental conditions.

[0006] Optionally, establishing an environmental wind speed prediction function for the area to be processed based on the air movement characteristics and the initial environmental detection data includes: The ambient wind speed prediction function satisfies the following relationship:

[0007] in, express The wind speed corresponding to the center of the processing area at a time point, Indicates the highest detection height of the processing area, Indicates the lowest detection height of the processing area, represents the wind shear index corresponding to the center of the processing area, represents the aerodynamic roughness, express exist The wind speed value corresponding to the time point, express exist The wind speed value corresponding to the time point.

[0008] The function of the present invention can realize the precision and intelligence of the wind speed prediction process, and provide a reliable information basis for environmental dust control.

[0009] Optionally, establishing an environmental dust concentration correction model based on the wind speed conditions, and obtaining environmental target monitoring information for the area to be treated based on the environmental dust concentration correction model and the initial environmental detection data, includes: establishing an environmental dust concentration correction model based on dust diffusion patterns and the wind speed conditions; obtaining dust concentration detection information for the area to be treated at different time points based on the initial environmental detection data; and processing the dust concentration detection information using the environmental dust concentration correction model to obtain environmental target monitoring information for the area to be treated. The present invention integrates real-time wind speed and dust diffusion patterns to further ensure the accuracy of dust concentration predictions, facilitating dust concentration analysis and equipment adjustment in different environments.

[0010] Optionally, establishing an ambient dust concentration correction model based on the dust diffusion law and the wind speed condition includes: The ambient dust concentration correction model satisfies the following relationship:

[0011] in, Indicates the processing area Dust concentration at a given time point, express The original dust concentration in the treatment area at a given time point, express The corresponding motion characteristic parameters, Indicates the geometric eigenvalue corresponding to the processing area, express Air flow in the treatment area at a given time point, express Parameter value corresponding to the average temperature of the processing area at a time point.

[0012] The model of the present invention can analyze the dust concentration at different time points, which is conducive to capturing and analyzing the concentration change trends and laws in different environments.

[0013] Optionally, setting a control instruction reference system in the automated dust suppression equipment includes: selecting control instruction reference indicators for the automated dust suppression equipment based on the operating principle of the automated dust suppression equipment and the environmental target monitoring information, the control instruction reference indicators including the spray particle size, jet length, and jet speed of the automated dust suppression equipment; and constructing the control instruction reference system for the automated dust suppression equipment based on the spray particle size, jet length, and jet speed. The present invention can dynamically adapt to environmental changes, adjust the control instruction reference system in real time based on environmental target monitoring information, and formulate and implement dust suppression plans for different environmental conditions and dust characteristics.

[0014] Optionally, the control reference index analysis results of the automated dust suppression equipment obtained based on the environmental target monitoring information and the control instruction reference system include: establishing a spray particle size analysis function, a jet length prediction function, and a jet speed calculation function in the control instruction reference system; and obtaining the control reference index analysis results of the automated dust suppression equipment through the spray particle size analysis function, the jet length prediction function, and the jet speed calculation function. The spray particle size analysis function, the jet length prediction function, and the jet speed calculation function of the present invention can be operated independently or deployed in conjunction with each other, seamlessly connecting with the system dust suppression equipment, and facilitating the effective treatment of environmental dust.

[0015] Optionally, said establishing a spray particle size analysis function, a spray length prediction function and a spray velocity calculation function in said control instruction reference system includes: The spray particle size analysis function satisfies the following relationship:

[0016] in, Indicates the droplet size of dust suppression equipment at different times, Indicates the processing area Dust concentration at a given time point, express The air velocity corresponding to the center of the processing area at a time point, express The wind speed corresponding to the center of the processing area at a time point, express Average dust particle size in the treatment area at a given time point, represents the constant term in the particle size analysis function, represents the dynamic viscosity of air, represents the inertial collision coefficient; The injection length prediction function satisfies the following relationship:

[0017] in, Indicates the range of dust suppression equipment at different times, represents the first fitting coefficient of the jet length prediction function, represents the second fitting coefficient of the jet length prediction function, represents the third fitting coefficient of the jet length prediction function, represents the ratio of the ejecta inertial force to the viscous force, Indicates the tension coefficient corresponding to the droplet size of dust suppression equipment at different times, Indicates the nozzle radius of the dust suppression equipment; The injection velocity calculation function satisfies the following relationship:

[0018] in, Indicates the average injection velocity of dust suppression equipment at different times, Indicates the initial injection velocity of dust suppression equipment at different times, represents the air density, Indicates the drag coefficient value, Indicates the droplet density of dust suppression equipment at different times, Indicates the average droplet size of dust suppression equipment at different times.

[0019] The present invention can accurately predict and control the operating parameters of the system dust suppression equipment based on the correlation analysis function, thereby ensuring the dust suppression effect in different environments.

[0020] Optionally, the adjustment and control of the automated dust suppression equipment in the treatment area based on the control reference index analysis results and the environmental target monitoring information to achieve effective dust control in the treatment area includes: adjusting and controlling the control instruction reference index of the automated dust suppression equipment in combination with the spray particle size analysis results, the injection length prediction results, the injection velocity calculation results, and the environmental target monitoring information to achieve effective dust control in the treatment area. The present invention controls environmental dust based on the environmental target monitoring information and the control reference index analysis results, improves the control effect of environmental dust, reduces resource consumption rate, and provides efficient and economical technical support for environmental dust control.

[0021] In a second aspect, in order to efficiently execute the automated dust suppression control method based on environmental data provided by the present invention, the present invention also provides an automated dust suppression control system based on environmental data, the system comprising an input device, a processor, an output device, and a memory, wherein the input device, the processor, the output device, and the memory are interconnected, the memory comprising the automated dust suppression control method based on environmental data as described in the first aspect of the present invention, the memory being used to store a computer program, the computer program comprising program instructions, and the processor being configured to call the program instructions. The automated dust suppression control system based on environmental data provided by the present invention has a compact structure, strong applicability, and greatly improves operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of the automatic dust suppression control method based on environmental data of the present invention; Figure 2 This is a structural diagram of the automatic dust suppression control system based on environmental data of the present invention. DETAILED DESCRIPTION

[0023] Specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the present invention. In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that these specific details are not necessarily required to practice the present invention. In other instances, well-known circuits, software, or methods are not specifically described to avoid obscuring the present invention.

[0024] Throughout this specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the present invention. Therefore, appearances of the phrases "in one embodiment," "in an embodiment," "an example," or "an example" in various places throughout this specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, or characteristics may be combined in any suitable combinations and / or subcombinations in one or more embodiments or examples. Furthermore, those of ordinary skill in the art will appreciate that the figures provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0025] See Figure 1 To address the limitations of current dust suppression methods in complex environments and meet the requirements for targeted, economical, and environmentally friendly dust control in practical applications, the present invention provides an automated dust suppression control method based on environmental data, which includes the following steps: S1. Use the environmental information monitoring and transmission module to obtain the initial environmental detection data of the area to be processed. The specific setting steps and implementation contents are as follows: First, various environmental data collection equipment and instruments are reasonably deployed in the area to be processed, and different data monitoring instruments are selected according to the environmental monitoring needs. The embodiment mainly covers information monitoring equipment such as temperature sensors, humidity sensors, air quality detectors, noise monitors, etc. Among them, the temperature sensor can sense the ambient temperature, and its measurement accuracy can reach to ensure the accuracy of temperature data in the area to be processed; the humidity sensor can monitor the air humidity in real time, and its fast response speed can reflect the fluctuation of environmental humidity in a short time; the air quality detector can simultaneously detect a variety of harmful gas components, including but not limited to sulfur dioxide, nitrogen oxides, particulate matter, etc., providing comprehensive data for environmental dust condition assessment; the noise monitor can accurately measure environmental noise conditions, which helps to effectively capture noise pollution.

[0026] In an optional embodiment, before environmental information monitoring and transmission, it is necessary to determine the location and number of information monitoring points based on the environmental characteristics and information monitoring needs of the area to be processed. After the information monitoring points are determined, various types of environmental data acquisition equipment are reasonably deployed according to the planning scheme. During the installation process, the relevant equipment must be operated strictly in accordance with relevant standards and specifications to ensure that the installation position of the system monitoring equipment is accurate and stable, further ensuring the accuracy of the initial environmental detection data.

[0027] The collected environmental data can be quickly transmitted to the control center of the environmental information monitoring and delivery module through data transmission equipment. The above-mentioned data transmission equipment can be a wired network, a wireless network, a LORA wireless module, etc. The wired network can effectively avoid signal interference and data loss during the data transmission process, ensuring the integrity and accuracy of the data, and is suitable for environmental scenarios with extremely high requirements for data transmission stability; the wireless network can be flexibly deployed and has a wide coverage range, and can quickly realize the remote transmission of environmental detection data, which is conducive to data collection at environmental monitoring points in different geographical locations; the low power consumption of the LORA wireless module can be transmitted over long distances, and is mainly used in remote areas or environmental areas with weak signal coverage, further ensuring the real-time transmission of environmental data.

[0028] At the same time, during the data transmission process, the data transmission equipment uses a variety of advanced technical means to ensure the real-time and accuracy of environmental monitoring data. Data encryption technology is used to encrypt the transmitted data to prevent the data from being stolen or tampered with during transmission. A data verification mechanism is used to verify the integrity of the received data. Once a data error is found, it is immediately retransmitted to ensure that the data received by the control center is accurate. At the same time, the data transmission equipment also has an automatic reconnection function. When the network is temporarily interrupted, it can automatically attempt to reconnect to ensure the continuity of data transmission. The above technologies enable the environmental information monitoring and transmission module to obtain initial detection data from different environments in a timely manner, providing an information basis for subsequent environmental dust treatment and governance decisions.

[0029] Furthermore, the method for obtaining the initial environmental detection data in the embodiment is only an optional condition of the present invention. In one or some other embodiments, the method for obtaining the initial environmental detection data can be optimized and adjusted according to the actual operating conditions of the environmental information monitoring and delivery module and the collection requirements of the environmental detection data. There are differences in the environmental conditions of different areas to be processed. By optimizing the acquisition method, the interference of the external environment on data collection can be effectively reduced, thereby obtaining more accurate initial environmental detection data, reducing the impact of data errors, and improving the accuracy and effectiveness of data monitoring results.

[0030] S2. Analyze the wind speed conditions in the area to be treated based on the initial environmental detection data, establish an environmental dust concentration correction model based on the wind speed conditions, and obtain environmental target monitoring information for the area to be treated based on the above environmental dust concentration correction model and the initial environmental detection data. The specific steps and implementation content are as follows: First, the wind speed conditions in the area to be treated are analyzed based on the initial environmental detection data.

[0031] Based on air movement characteristics and initial environmental detection data, a wind speed prediction function is established for the area to be processed. This function is then used to analyze the wind speed results corresponding to different times in the area to be processed. The wind speed conditions in the area to be processed are then analyzed by combining these results with the initial environmental detection data.

[0032] Dust concentration test results are easily affected by external environmental factors. During the dust concentration test process, parameters such as ambient wind speed and temperature can interfere with the results, with wind speed having the most significant impact. Therefore, accurately measuring ambient wind speed and appropriately compensating the dust test results based on wind speed is beneficial for obtaining more accurate dust concentration results. Therefore, targeted analysis and prediction of ambient wind speed under different environmental conditions is necessary.

[0033] In the embodiment, an environmental wind speed information correction coefficient is introduced based on historical wind speed information and environmental conditions, and the environmental wind speed information in the initial environmental detection data is corrected based on the environmental wind speed information correction coefficient. The above-mentioned environmental wind speed information correction coefficient can adjust and calibrate the measured environmental wind speed information, aiming to obtain more accurate wind speed information under specific environments. The calculation of the correction coefficient is a multi-factor comprehensive analysis process, involving meteorological elements such as ambient temperature, humidity, and air pressure, as well as parameters such as the installation angle and position of the anemometer. The above-mentioned factors are intertwined and jointly affect the deviation between the measured wind speed information and the actual wind speed information. Therefore, it is necessary to set the information correction coefficient based on the specific application scenario and actual environmental conditions, and select and correct the relevant environmental wind speed information to improve the accuracy and feasibility of wind speed information under different environmental conditions.

[0034] Therefore, the wind speed monitoring information set is obtained based on the environmental wind speed information correction coefficient, the environmental initial detection data and the data collection time, where the data collection time satisfies the following relationship: , the wind speed monitoring information set satisfies the following relationship ,in Represents the wind speed monitoring information set under different environmental conditions, Indicates the wind speed monitoring information corresponding to the collection time 1, Indicates the wind speed monitoring information corresponding to the collection time 2, Indicates the collection time Corresponding wind speed monitoring information.

[0035] Furthermore, the wind shear index corresponding to the center of the processing area is analyzed based on the above wind speed monitoring information set.

[0036] At the surface layer, wind speed varies with altitude, following a logarithmic or exponential distribution due to factors such as surface friction. In the field of dust monitoring and treatment, the height distribution of wind fields influences the movement and diffusion of dust. Based on wind speed monitoring data, the wind shear index corresponding to the center of the treatment area can be determined. This index helps understand the dust diffusion mechanism in the area and develop dust control strategies.

[0037] The wind shear index corresponding to the center of the above processing area needs to satisfy the following relationship:

[0038] in, represents the wind shear index corresponding to the center of the processing area, Indicates the processing area The horizontal average wind speed at Indicates the processing area The horizontal average wind speed at Indicates the highest detection height of the processing area, Indicates the minimum detection height of the dust handling area, Indicates the weight index corresponding to the center height of the processing area.

[0039] The wind shear index describes how wind speed varies with altitude. Near the ground, wind speed increases with altitude due to surface friction and environmental factors. The wind shear index is used to quantify this relationship.

[0040] The wind shear index reflects how quickly wind speed changes with altitude. A larger wind shear index means wind speed increases rapidly with altitude, while a smaller wind shear index indicates a more gradual change in wind speed. In dust handling areas, the wind shear index is crucial for predicting dust movement and dispersion.

[0041] The horizontal average wind speed refers to the average value of the wind speed in the horizontal direction within a certain period of time. The horizontal average wind speed measured at the highest and lowest detection points in the dust treatment area is an important parameter for calculating the wind shear index, which further reflects the magnitude of the wind speed at the highest and lowest points in the dust treatment area. By comparing the difference in wind speed magnitude, it is helpful to analyze the change of wind speed with height. In the embodiment, electronic anemometers such as cup anemometers, ultrasonic waves, and lasers can be used to directly measure the wind speed at a specific height and calculate the average wind speed in a certain period of time in the treatment area, that is, to perform weighted averaging on the data of multiple measurement points to obtain the average wind speed at different heights in the area. In the embodiment, the horizontal average wind speed satisfies the following relationship:

[0042] in, represents the horizontal average wind speed at any height within the treatment area, Indicates the processing area The horizontal wind speed corresponding to the height in the first time period, Indicates the processing area The horizontal wind speed corresponding to the height in the second time period, Indicates the processing area The horizontal wind speed corresponding to the height in the nth time period, Indicates that The total height monitoring time is divided into n time periods.

[0043] Based on this, the horizontal average wind speed corresponding to the highest detection height and the lowest detection height in the processing area can be obtained. Through the above calculation method, the method of obtaining the average wind speed can be standardized, so that the calculation results of the wind shear index have higher accuracy and reliability.

[0044] The highest detection height of the processing area indicates the highest height for wind speed detection in the dust processing area, and the lowest detection height of the dust processing area indicates the lowest height for wind speed detection in the dust processing area. This helps to understand the trend of wind speed changes with height.

[0045] The above-mentioned weight index is used to quantify the relative importance of the center height of the dust treatment area in the calculation or analysis. During the calculation of the wind shear index, different heights have different degrees of influence on the calculation results, which can more accurately reflect the change pattern of wind speed with height and the contribution of data at different heights to the overall analysis results.

[0046] By accurately calculating the wind shear index, the movement and diffusion of dust in the treatment area can be predicted more accurately. The wind shear index reflects how quickly wind speed changes with altitude. A larger wind shear index means that wind speed increases rapidly with altitude, and the dust diffusion range may be wider; a smaller wind shear index means that wind speed changes slowly and dust diffusion is relatively concentrated. Based on this, dust control equipment can be arranged according to different environmental conditions, which is conducive to improving the environmental dust treatment effect.

[0047] On the basis of using the environmental information monitoring and transmission module to monitor the key parameters such as dust concentration, wind speed, wind direction in the environment in real time, in order to more accurately analyze the actual wind speed conditions in the dust treatment area, the wind speed will be affected by the environmental factors of the dust treatment area during the movement. In the embodiment, the environmental wind speed is further analyzed based on the Pythagorean principle of vector decomposition, the wind shear index in the center of the treatment area and the initial environmental detection data, and then the environmental wind speed prediction function in this embodiment is constructed.

[0048] The above ambient wind speed prediction function satisfies the following relationship:

[0049] in, express The wind speed corresponding to the center of the processing area at a time point, Indicates the highest detection height of the processing area, Indicates the lowest detection height of the processing area, represents the wind shear index corresponding to the center of the processing area, represents the aerodynamic roughness, express exist The wind speed value corresponding to the time point, express exist The wind speed value corresponding to the time point.

[0050] The wind speed corresponding to the center of the treatment area at different time points refers to the wind speed at the center of the dust treatment area at a specific time point. It comprehensively considers multiple factors such as the wind speed difference at different heights in the area, wind shear index, aerodynamic roughness, etc., and is of great significance for understanding the wind field characteristics of the area to be treated, the risk of dust diffusion, and the formulation of control strategies.

[0051] In the dust treatment area, in order to monitor the changes in wind speed with the height of the environment, detection points at different heights are set up. The height of the highest detection point reflects the upper limit of the wind speed detection in the dust treatment area. By monitoring the wind speed at this height, the flow of upper air can be understood, providing an important basis for analyzing the wind field characteristics of the entire area.

[0052] The lowest detection height in the treatment area is the lowest height for wind speed detection in the treatment area. It represents the lower limit of wind speed detection and reflects the wind speed conditions near the ground layer. Due to the influence of factors such as surface friction, the wind speed information near the ground layer can be obtained based on this, which helps to more comprehensively understand the wind field distribution conditions in the dust treatment area.

[0053] The wind shear index is a parameter that describes how wind speed varies with altitude. Near the ground, wind speed increases with altitude due to surface friction and external environmental factors. The wind shear index quantifies this relationship. A larger wind shear index indicates a rapid increase in wind speed with altitude, while a smaller wind shear index indicates a more gradual change in wind speed with altitude. In dust processing areas, the wind shear index is crucial for predicting dust movement and dispersion. Accurately calculating the wind shear index provides a better understanding of the spatial distribution of wind speed.

[0054] Aerodynamic roughness reflects the impact of surface roughness on wind speed. Surface features vary under different environmental conditions, such as vegetation, buildings, and topography. These features create friction and resistance to air flow, thereby affecting the magnitude and distribution of wind speed. The greater the aerodynamic roughness, the greater the surface's resistance to wind speed and the more pronounced the wind speed attenuation near the ground. Incorporating aerodynamic roughness into environmental wind speed forecasts can make predictions more realistic and improve their accuracy.

[0055] Aerodynamic roughness is an important parameter that measures the effect of surface roughness on wind speed. Its calculation formula must be combined with the specific measurement method and the type of environmental surface. The calculation method of aerodynamic roughness in the embodiment satisfies the following relationship:

[0056] in, represents the aerodynamic roughness, represents the von Karman constant, express The average wind speed corresponding to the processing area at the time point, represents the atmospheric stability correction function, represents the surface roughness cover density in the treatment area, Indicates the average height of the top of the vegetation canopy in the treatment area. Represents the characteristic length scale within the atmospheric boundary layer near the ground.

[0057] The wind speed at the highest detection height in the processing area at a specific time point reflects the flow intensity of the upper air at a given time. By monitoring the wind speed at high detection heights at different time points, we can understand the change pattern of wind speed over time and provide data support for analyzing the dynamic characteristics of the wind field.

[0058] The wind speed at the lowest detection height in the processing area reflects the wind speed conditions near the ground layer and is greatly affected by factors such as surface friction. Data monitoring helps to understand the changing characteristics of the wind speed near the ground layer and the degree of influence of surface characteristics on wind speed.

[0059] The ambient wind speed prediction function comprehensively considers multiple factors, including the highest and lowest detection altitudes within the treatment area, wind shear index, aerodynamic roughness, and wind speed values at different altitudes at different time points. These parameters can be used to determine the wind speed at the center of the treatment area at a specific time point. This provides an effective mathematical prediction model for the wind field characteristics of the dust treatment area, helps better understand the spatial and temporal distribution of wind speed, and provides a scientific basis for decision-making regarding dust control and environmental protection.

[0060] Then, an ambient dust concentration correction model is established based on the wind speed conditions.

[0061] An environmental dust concentration correction model is established based on the dust diffusion law and the wind speed conditions; and dust concentration detection information at different time points in the area to be processed is obtained based on the initial environmental detection data.

[0062] After completing the accurate prediction of the ambient wind speed, in order to further explore the dust diffusion and distribution laws in the area to be treated, it is necessary to establish an ambient dust concentration correction model based on the wind speed conditions. The construction of this model is closely centered around the dust diffusion laws and wind speed conditions. Comprehensive consideration of multiple influencing factors can more accurately reflect the dynamic changes in dust concentration in the actual environment.

[0063] Based on the fundamental principles of dust dispersion, we analyzed how wind speed affects dust trajectory, diffusion range, and settling rate. Combined with the aforementioned ambient wind speed prediction function, we effectively analyzed the inherent relationship between wind speed at the center of the treatment area and dust diffusion at different time points. This integrated analysis of the treatment area's topography, surrounding building layout, and meteorological conditions led to the development of an ambient dust concentration correction model.

[0064] In order to obtain the various parameters required for the correction model, the embodiment uses the initial environmental detection data and data analysis method to monitor and record the dust concentration in the area to be treated at different time points in real time, thereby obtaining the dust concentration detection information at different time points in the area to be treated. The above information provides important data support for the construction and verification of the model.

[0065] Finally, the above ambient dust concentration correction model satisfies the following relationship:

[0066] in, Indicates the processing area Dust concentration at a given time point, express The original dust concentration in the treatment area at a given time point, express The corresponding motion characteristic parameters, Indicates the geometric eigenvalue corresponding to the processing area, express Air flow in the treatment area at a given time point, express Parameter value corresponding to the average temperature of the processing area at a time point.

[0067] Dust concentrations in the dust treatment area at different time points refer to dust analysis results calculated using a modified model. These reflect the actual dust concentration level in the treatment area at a specific point in time, taking into account various influencing factors such as wind speed, air flow, and temperature. Compared to raw dust concentrations, these more accurately describe actual dust conditions in the environment and are crucial for assessing the extent of dust pollution and developing appropriate control measures.

[0068] The original dust concentration in the treatment area at different time points refers to the dust concentration in the treatment area at different time points without considering influencing factors such as wind speed, air flow, and temperature. The above original dust concentration can be obtained through direct environmental monitoring means.

[0069] The corresponding motion characteristic parameters are related to the environmental motion variables, and factors such as the actual wind speed, tangential speed or average wind speed of the environment will affect them. In the embodiment, the function right After processing, we get The corresponding motion characteristic parameters can describe the motion state of the wind speed in the center of the processing area at different time points.

[0070] Motion characteristic parameters are one of the key factors influencing dust diffusion and distribution. Wind speed affects the suspension time of dust particles in the air. Higher wind speeds make dust particles more likely to remain suspended in the air, while lower wind speeds may cause dust particles to settle more quickly. Wind speed also changes the diffusion range and rate of dust particles. Higher wind speeds increase the potential for a wider diffusion range. Wind speed also affects the settling rate of dust particles. Under different wind speed conditions, the settling mechanism of dust particles varies, affecting their residence time and distribution in the air. Motion characteristic parameters need to be determined based on the actual conditions of different environments. Physical models and experimental data fitting are used to adjust these motion characteristic parameters for different environments.

[0071] Geometric eigenvalues can describe the geometric characteristics of objects, regions or shapes in the three-dimensional space of the processing area, and are used to quantify the shape, size, direction or topological structure of different environmental areas. The size of the geometric eigenvalue depends on factors such as the environmental area, perimeter, volume, aspect ratio, curvature, fractal dimension, etc.

[0072] Since the geometric shape and size of the dust treatment area will affect the diffusion and distribution of dust, the geometric eigenvalues are mainly used to describe the spatial form of the treatment area. Different geometric eigenvalues will have different effects on the dust diffusion path, diffusion range and concentration distribution.

[0073] Air flow rate represents the rate of change of the volume or mass of air passing through a certain cross section in the processing area at different time points over time. The calculation method depends on the specific application scenario and the measurement parameters available in the environment. The calculation method of the air flow rate in the embodiment satisfies the following relationship:

[0074] in, express Air flow in the treatment area at a given time point, represents the air flow coefficient, represents the cross-sectional area corresponding to the center of the processing area, express The wind speed corresponding to the center of the processing area at a time point.

[0075] The air flow rate in the treatment area at different points in time reflects the flow of air within the area and plays a significant role in the dispersion and dilution of dust. When the air flow rate is high, the air moves faster, carrying dust particles farther and making them more easily diluted, thereby reducing the dust concentration in the local area. Conversely, when the air flow rate is low, the air moves slower, causing dust particles to accumulate more easily in the local area, leading to higher dust concentrations. This air flow rate is primarily measured and calculated using equipment such as wind speed measuring instruments and flow meters.

[0076] Temperature affects the physical properties of dust and the flow characteristics of air, thereby indirectly affecting the concentration distribution of dust. Converting the actual temperature value into a parameter that affects the dust concentration can provide feedback on the impact of temperature on the air flow speed and direction.

[0077] The above-mentioned ambient dust concentration correction model comprehensively considers the impact of multiple factors on dust concentration. It incorporates motion characteristic parameters, geometric eigenvalues, air flow, and temperature parameters to correct the original dust concentration, thereby obtaining a more accurate dust concentration result for the treatment area. This model can be used to predict changes in dust concentration in the treatment area at different time points and under different environmental conditions, providing a scientific basis for dust pollution control and the control of system dust suppression equipment.

[0078] Finally, based on the above-mentioned environmental dust concentration correction model and the initial environmental detection data, the environmental target monitoring information of the area to be treated is obtained.

[0079] The dust concentration monitoring information of the center point of the dust treatment area at different times is obtained based on the initial environmental detection data. In the embodiment, several time points are randomly selected, and the time points satisfy the following relationship , , , , and the initial information of dust concentration measured during the monitoring process can be found in Table 1.

[0080] Table 1 Initial information of dust concentration at the center of the dust treatment area at different times

[0081] The dust information monitoring angles in Table 1 are based on the angles of the surface level of the area to be treated, where , , , These are four monitoring time points randomly selected based on the initial environmental detection data.

[0082] Based on the initial dust concentration data at different times at the center of the dust treatment area in Table 1, as well as the wind speed analysis results for the center of the area, the dust concentration correction model was used to further integrate and process the relevant information, and finally the dust concentration correction analysis results of the treatment area were obtained.

[0083] The wind speed collection time point t, and its corresponding wind speed monitoring result is recorded as At the same time, the original dust concentration at the collection time point t is obtained based on the table information In the embodiment, it is necessary to obtain the original dust concentration corresponding to different time points based on the original dust information at different monitoring angles at the same time point.

[0084] Right now The original dust concentration in the treatment area at a given time point satisfies the following relationship:

[0085] in, express The original dust concentration in the treatment area at a given time point, express The original dust concentration corresponding to the 0° monitoring angle in the treatment area at the time point, express The original dust concentration corresponding to the 45° monitoring angle in the treatment area at the time point, express The original dust concentration corresponding to the 90° monitoring angle in the treatment area at the time point, express The original dust concentration corresponding to the 1800° monitoring angle in the treatment area at the time point.

[0086] Subsequently, the above-mentioned dust concentration detection information was systematically processed using the environmental dust concentration correction model. The model comprehensively considers the impact of multiple factors such as wind speed and initial dust concentration on dust concentration distribution, and fully considers the interactive relationship and influence of factors such as environmental wind speed and initial dust concentration on dust concentration distribution. After model calculation and analysis, the corrected dust concentration information of the treatment area at different time points was obtained. Furthermore, the corrected dust concentration information was integrated with other environmental information in the initial environmental detection data to obtain the environmental target monitoring information of this embodiment. The above-mentioned implementation steps provide information basis for judging the dust condition of the treatment area and regulating the system dust suppression equipment.

[0087] Furthermore, the analysis method and acquisition steps of the environmental target monitoring information in this embodiment are only an optional condition of the present invention. In one or some other embodiments, the analysis method of the environmental target monitoring information can be optimized according to the actual monitoring situation of the dust information and the processing requirements of the initial environmental detection data, which can better fit the data characteristics under different monitoring scenarios, thereby improving the accuracy and reliability of the monitoring information analysis results, so as to ensure that high-quality environmental target monitoring information can be obtained under different environmental conditions.

[0088] S3. Set up a control instruction reference system in the automated dust suppression equipment. Based on the environmental target monitoring information and the control instruction reference system, obtain the control reference index analysis results of the automated dust suppression equipment. The specific implementation contents are as follows: Firstly, based on the working principle of the automatic dust suppression equipment and the environmental target monitoring information, the control instruction reference indicators of the automatic dust suppression equipment were selected. The above control instruction reference indicators mainly include the spray particle size, injection length and injection speed of the automatic dust suppression equipment; then, the control instruction reference system of the automatic dust suppression equipment was constructed based on the spray particle size, injection length and injection speed.

[0089] This embodiment deeply analyzes the working principle and operation mechanism of the automated dust suppression equipment, and combines the key information such as dust concentration distribution and diffusion trend reflected by the environmental target monitoring information to select the control instruction reference indicators of the automated dust suppression equipment. The above reference indicators mainly include the spray particle size, injection length and injection speed of the system's automated dust suppression equipment. The spray particle size directly determines the collision efficiency between droplets and dust particles, affecting the environmental dust suppression effect; the injection length is related to the range of action of the dust suppression equipment, which is crucial for dust suppression in large areas; the injection speed affects the kinetic energy and coverage of the droplets, and is an important factor in ensuring the dust suppression effect and uniformity.

[0090] Furthermore, based on the three key indicators of spray particle size, spray length and spray speed, a systematic, comprehensive and targeted reference system for control instructions of automated dust suppression equipment was constructed.

[0091] During the construction process, the differences in dust characteristics under different environmental conditions, the limitations of equipment performance, and the actual needs of dust suppression operations were fully considered. Based on the analysis of relevant experimental data and simulation calculation results, the reasonable value range of each indicator and the matching relationship between them were determined. This reference system provides a reference basis for the precise control of automated dust suppression equipment, and helps to optimize dust suppression measures and equipment operation plans in different environments, thereby providing support for environmental quality improvement and dust pollution control.

[0092] The control instruction reference system in the embodiment is shown in Table 2.

[0093] Table 2 Control instruction reference system information table for automated dust suppression equipment

[0094] The embodiment clearly defines the three key indicators of spray particle size, injection length and injection speed as the key indicators of the control instruction reference system, which comprehensively covers factors affecting the performance and effect of automated dust suppression equipment, and can monitor and control the equipment from multiple dimensions, thereby providing a scientific basis for the control of automated dust suppression equipment, and helping the system equipment to adjust parameters such as spray particle size, injection length and injection speed according to different environmental conditions and operational requirements, thereby achieving dust treatment and control under different environmental conditions.

[0095] Then, the spray particle size analysis function, jet length prediction function and jet velocity calculation function were established in the control instruction reference system.

[0096] Within the framework of the control instruction reference system, a spray particle size analysis function, a jet length prediction function, and a jet velocity calculation function were further constructed, aiming to quantitatively analyze the key indicator parameters of the control instruction reference system, which will help to achieve precise control of the operating status of automated dust suppression equipment and provide more scientific and systematic theoretical support for optimizing the dust suppression effect.

[0097] In order to accurately analyze the droplet size of the automated dust suppression equipment at different times, a spray particle size analysis function is constructed in the embodiment. Based on this, the change in the droplet size of the automated dust suppression equipment at different times can be quantified. The above-mentioned spray particle size analysis function satisfies the following relationship:

[0098] in, Indicates the droplet size of dust suppression equipment at different times, Indicates the processing area Dust concentration at a given time point, express The air velocity corresponding to the center of the processing area at a time point, express The wind speed corresponding to the center of the processing area at a time point, express Average dust particle size in the treatment area at a given time point, represents the constant term in the particle size analysis function, represents the dynamic viscosity of air, represents the inertial collision coefficient; The droplet size of dust suppression equipment at different times refers to the droplet size produced by the dust suppression equipment at different times. The unit can be set according to actual needs, such as microns, nanometers, etc. The droplet size directly reflects the fineness of the spray of the dust suppression equipment at a specific moment, and plays a vital role in the environmental dust suppression effect.

[0099] The dust concentration in the treatment area at different time points determines the difficulty and demand of dust suppression and is one of the important factors affecting the selection of droplet size.

[0100] The air flow rate corresponding to the center of the treatment area at different time points will affect the movement trajectory and diffusion range of the droplets in the air, and thus affect the distribution of droplet particle size.

[0101] The wind speed and air velocity corresponding to the center of the treatment area at different time points work together to determine the residence time and effect of the droplets in the treatment area.

[0102] The average dust particle size in the treatment area at different time points directly affects the collision efficiency between droplets and dust particles. Therefore, the droplet size needs to be adjusted according to the characteristics of the dust particle size.

[0103] The constant term in the particle size analysis function needs to be further determined through experimental data and theoretical analysis. It can be used to correct the influence of other parameters in the spray particle size analysis function on the droplet size calculation results, ensuring the accuracy and reliability of the function analysis results.

[0104] Aerodynamic viscosity reflects the flow characteristics of air and has a significant impact on the movement and diffusion of droplets in the air. The aerodynamic viscosity of the treatment area needs to satisfy the following relationship:

[0105] in, represents the dynamic viscosity of air, express The dynamic viscosity of the air in the treatment area is express The actual temperature of the treatment area at a given time point, represents the reference temperature of the treatment area, represents the Satran constant.

[0106] The inertial collision coefficient comprehensively considers factors such as the inertia, shape, and density of droplets and dust particles, and is mainly used to describe the collision probability and interaction relationship between droplets and dust particles.

[0107] The spray particle size analysis function can quantify the changes in droplet size of automated dust suppression equipment at different times. Since dust concentration at different points in time is a key factor in determining the difficulty and demand for dust suppression, the spray particle size analysis function adjusts droplet size based on real-time dust concentration. This allows dust suppression equipment to produce droplets of the appropriate size at specific moments based on actual dust suppression needs, precisely meeting dust suppression requirements at different times and improving dust suppression efficiency and performance under various environmental conditions.

[0108] In this example, a jet length prediction function was constructed to analyze the jet length characteristics of automated dust suppression equipment at different time points. Based on the derivation and verification of experimental data and theoretical analysis, a jet length prediction function was established. This function can accurately quantify the jet length of automated dust suppression equipment at different time points, providing a basis for subsequent dust suppression effect evaluation and equipment control.

[0109] The above jet length prediction function satisfies the following relationship:

[0110] in, Indicates the range of dust suppression equipment at different times, represents the first fitting coefficient of the jet length prediction function, represents the second fitting coefficient of the jet length prediction function, represents the third fitting coefficient of the jet length prediction function, represents the ratio of the ejecta inertial force to the viscous force, Indicates the tension coefficient corresponding to the droplet size of dust suppression equipment at different times, Indicates the nozzle radius of the dust suppression equipment; The range of dust suppression equipment at different times directly reflects the maximum horizontal distance the device's spray (e.g., droplets) can reach at a specific point in time. The range directly determines the area of effect of dust suppression equipment and is a key indicator for evaluating its performance and effectiveness. In dust control in various environments, a longer range means the device can cover a wider area, effectively suppressing the spread of ambient dust.

[0111] The three fitting coefficients of the spray length prediction function are empirical constants, derived from experimental data. They comprehensively consider the impact of multiple factors on spray length and provide an overall regulatory effect. Different fitting coefficients are required for different dust suppression equipment, operating environments, and spray characteristics. The coefficient values need to be adjusted based on the actual spray length of different dust suppression equipment to ensure that the prediction function can accurately predict the spray length of droplets of different particle sizes.

[0112] The ratio of the inertial force of the ejecta to the viscous force is a dimensionless parameter in fluid mechanics and can be used to describe the flow state of the fluid related to the dust suppression equipment. It reflects the relative magnitude of the inertial force and viscous force of the spray (droplets). When the value of is large, the inertial force plays a dominant role, the movement of the droplets in the air tends to be more linear, and the range will be relatively long; when When the value is small, the viscosity has a greater impact, the droplets are easily affected by air resistance and quickly decelerate, and the range is correspondingly shortened. The size of the jet is related to factors such as the speed, density, viscosity of the ejecta and the density and viscosity of the air.

[0113] In the spray dust suppression scenario, the tension coefficient Droplet size of dust suppression equipment at different times The dynamic surface tension of the spray liquid is linearly correlated with the droplet size. The tension coefficient corresponding to the droplet size of the dust suppression equipment at different times is a parameter value related to the droplet size. The smaller the droplet size, the larger its surface area, and the more significant the effect of surface tension on the movement and diffusion of the droplets. Smaller droplets are more susceptible to Brownian motion and air turbulence in the air, resulting in a more complex trajectory and a certain degree of limitation in their range. Larger droplets, on the other hand, have greater inertia and are less affected by surface tension, resulting in more stable movement and potentially longer range. Therefore, the tension coefficient can comprehensively consider the complex influence of droplet size on spray length.

[0114] The nozzle radius is a structural parameter of dust suppression equipment that directly affects the initial velocity and flow rate of the spray. According to the principles of fluid mechanics, a larger nozzle radius results in a lower initial velocity but a higher flow rate. A smaller nozzle radius results in a higher initial velocity but a lower flow rate. The relationship between spray length and nozzle radius can be expressed using a correlation function and the nozzle radius: All other conditions being equal, a larger nozzle radius increases spray length.

[0115] The jet length prediction function accurately calculates the range of dust suppression equipment at different times. This allows automated dust suppression control methods to predict the effective range of different equipment in specific environments. This allows for the rational planning of the system's dust suppression equipment layout, operating parameters, and operating times, maximizing dust suppression effectiveness under varying environmental conditions. Furthermore, the above prediction function can adapt to different environments and equipment characteristics. In practical applications, the fitting coefficients in the prediction function can be dynamically adjusted based on actual environmental conditions such as temperature, humidity, and air density, as well as equipment parameters such as nozzle type and jet pressure, making the prediction results more accurate and reliable.

[0116] In this example, a jet length prediction function was constructed to analyze the average jet velocity of automated dust suppression equipment at different time points. This function accurately quantifies the average jet velocity of automated dust suppression equipment at different times, providing information for subsequent equipment optimization and control, as well as environmental dust suppression effectiveness evaluation.

[0117] The above injection velocity calculation function satisfies the following relationship:

[0118] in, Indicates the average injection velocity of dust suppression equipment at different times, Indicates the initial injection velocity of dust suppression equipment at different times, represents the air density, Indicates the drag coefficient value, Indicates the droplet density of dust suppression equipment at different times, Indicates the average droplet size of dust suppression equipment at different times.

[0119] The average injection velocity of dust suppression equipment at different times refers to the average movement speed of droplets ejected by automated dust suppression equipment under specific conditions at different time points. It directly reflects the ability and efficiency of droplets to propagate in the air during the actual operation of the dust suppression equipment. The above speed plays an important role in the evaluation of dust suppression effects. A higher average injection velocity means that droplets can reach a farther distance, thereby expanding the dust suppression range and improving dust suppression efficiency.

[0120] The initial injection velocity of dust suppression equipment at different times refers to the initial velocity of droplets ejected from the dust suppression equipment at a specific point in time. This initial injection velocity is a key factor influencing the average injection velocity and is primarily determined by the dust suppression equipment's structural parameters, such as nozzle shape, size, and injection pressure. A higher initial injection velocity can impart greater kinetic energy to the droplets, helping to overcome air resistance and, therefore, increasing the average injection velocity to a certain extent.

[0121] Air density refers to the mass of air per unit volume and is a physical property of air. This air density has a significant impact on the movement of droplets. In environments with higher air density, droplets experience greater air resistance, which slows their movement and reduces their average spray velocity. Air density is affected by factors such as temperature, humidity, and air pressure. In environments with high temperature, low humidity, and low pressure, air density is lower, resulting in less resistance for droplets, which helps increase their average spray velocity.

[0122] The drag coefficient is a dimensionless factor that describes the drag experienced by a droplet as it moves through the air. This value is dependent on factors such as the droplet's shape, size, surface roughness, and air flow conditions. The more irregular the droplet's shape and the rougher its surface, the greater the drag coefficient and the greater the drag experienced by the droplet.

[0123] The drag coefficient is the ratio of the resistance to the object to the dynamic pressure of the fluid and the reference area. The drag coefficient value in the embodiment satisfies the following relationship:

[0124] Where, represents the drag coefficient value, Indicates the total resistance value of the droplets in the air. represents the cross-sectional area corresponding to the center of the processing area, represents the predicted density of droplets from dust suppression equipment, Indicates the speed of the droplets relative to the air.

[0125] The droplet density of dust suppression equipment at different times refers to the mass per unit volume of droplets ejected by the dust suppression equipment at a specific point in time. Droplet density is related to factors such as the concentration of the spray liquid and the atomization effect. A higher droplet density means that the droplets contain more water or dust suppressant, which increases the mass of the droplets and thus affects the droplet movement speed to a certain extent. Droplet density also affects the droplet settling speed and diffusion range, affecting the dust suppression effect in the environment.

[0126] The average droplet size of dust suppression equipment at different times refers to the average diameter of the droplets ejected by the dust suppression equipment at a specific point in time. Average droplet size is a key factor influencing average spray velocity. Smaller droplets have a larger specific surface area and experience greater air resistance, slowing their movement and reducing average spray velocity. Furthermore, average droplet size affects droplet settling rate and diffusion range. Smaller droplets are more likely to suspend and diffuse in the air, thereby expanding the dust suppression range, but are more susceptible to airflow and deflection from the spray direction.

[0127] The injection velocity calculation function comprehensively considers the impact of multiple factors, including initial injection velocity, air density, drag coefficient, droplet density, and average droplet size, on the average injection velocity of dust suppression equipment at different times. Calculating the average injection velocity through this function provides a basis for equipment control and optimization.

[0128] Then, the control reference index analysis results of the automated dust suppression equipment are obtained through the spray particle size analysis function, the injection length prediction function and the injection velocity calculation function.

[0129] In this embodiment, the droplet particle size of the dust suppression equipment at different times is obtained using the spray particle size analysis function; the range of the dust suppression equipment at different times is obtained through the injection length prediction function; the average injection velocity of the dust suppression equipment at different times is obtained based on the injection velocity calculation function; based on this, the control reference index analysis results of the automated dust suppression equipment can be accurately obtained.

[0130] During the actual operation of the performance and control strategy of the automated dust suppression equipment, a comprehensive analysis and evaluation of the operating status of the equipment at different time points is carried out based on the spray particle size analysis function, injection length prediction function, and injection velocity calculation function in the control instruction reference system.

[0131] The spray particle size analysis function comprehensively considers factors such as the physical properties of the spray liquid, the structural parameters of the atomization device, and environmental factors. It analyzes the droplet particle size sprayed by the dust suppression equipment at different times and can accurately reflect the change pattern of the droplet particle size under different conditions. It provides a basis for the performance evaluation of dust suppression equipment and the formulation of dust suppression strategies.

[0132] At the same time, the spray length prediction function predicts the range of dust suppression equipment at different times based on factors such as the initial spray conditions of the equipment, aerodynamic characteristics, and the interaction between droplets and air. The range prediction results of the dust suppression equipment can provide a reference for equipment layout and operation parameter adjustment.

[0133] In addition, the injection velocity calculation function comprehensively considers factors such as the initial injection velocity, air resistance, and droplet characteristics, and calculates the average injection velocity of the dust suppression equipment at different times. It fully considers the complex conditions in the actual operation of dust treatment, can truly reflect the injection performance of the equipment, and provides information support for equipment control and optimization.

[0134] Based on the analysis results of relevant functions in the comprehensive control instruction reference system, key parameters such as droplet particle size, range and average injection velocity were systematically integrated and deeply analyzed, and the control reference index analysis results of the automated dust suppression equipment were obtained. The above results not only cover the operating performance evaluation of the equipment at different time points, but also provide a reference basis and information support for equipment optimization design, operating parameter adjustment and dust control strategy formulation, which will help to improve the dust suppression efficiency of the equipment, reduce operating costs, and promote the practical application of automated dust suppression technology.

[0135] Furthermore, the analysis method of the control indicators of the dust suppression equipment in this embodiment is only an optional condition of the present invention. In one or some other embodiments, the analysis method of the control indicators can be adjusted according to the actual operation mechanism of the dust suppression equipment and the requirements for handling environmental dust. In the actual application environment, optimizing the analysis method, parameters and calculation model for the equipment operation mechanism and dust characteristics can more accurately reflect the performance of the system equipment under different working conditions, and provide a more reliable information basis for dust suppression solutions and equipment control strategies.

[0136] S4. Adjust and control the automated dust suppression equipment in the treatment area based on the control reference index analysis results and environmental target monitoring information to achieve effective dust control in the treatment area. The specific implementation contents are as follows: Combined with the spray particle size analysis results, injection length prediction results, injection velocity calculation results and environmental target monitoring information, the control instruction reference indicators of the automated dust suppression equipment are adjusted and controlled to achieve effective control of dust in the processing area.

[0137] After obtaining the spray particle size analysis results, spray length prediction results, spray velocity calculation results, and environmental target monitoring information, the relevant analysis results are integrated and analyzed. For the spray particle size analysis results, it is important to focus not only on the average particle size but also to analyze the uniformity of the particle size distribution. This uniform particle size distribution helps improve the spray coverage and dust reduction efficiency. Based on this analysis, the atomization parameters of the automated dust suppression equipment are adjusted, including the atomizer pressure, flow rate, and nozzle aperture, to optimize the spray particle size generation effect.

[0138] When predicting spray length, it's important to consider the impact of environmental factors such as wind speed, direction, temperature, and humidity on the spray process. In environments with high wind speeds, the spray pressure can be appropriately increased to extend the spray length, ensuring the spray accurately covers the target area being treated. Furthermore, numerical simulation technology can be used to predict and correct the spray trajectory in real time, dynamically adjusting the spray angle and direction based on the predictions, thereby improving the spray accuracy of the system equipment.

[0139] The calculated spray velocity is crucial for controlling the impact and coverage of the spray. The spray velocity range should be appropriately set based on the specific dust characteristics and environmental dust treatment requirements. For fine dust, the spray velocity can be appropriately reduced to increase the spray's residence time in the air, thereby improving the dust reduction effect. For larger dust particles, the spray velocity can be appropriately increased to enhance the spray's impact and further promote dust settling.

[0140] Environmental target monitoring information mainly covers multiple aspects such as dust concentration, air quality index, and meteorological parameters. By combining the above information to establish an intelligent decision-making model in the automated dust suppression control system, the dust pollution status of the area to be treated can be evaluated in real time, and the operating mode and parameters of the automated dust suppression equipment can be automatically adjusted according to the evaluation results. In an optional embodiment, when the dust concentration is detected to exceed the preset environmental threshold, the operating frequency and spray volume of the system dust suppression equipment are automatically increased. When the meteorological conditions change, the operating strategy of the system dust suppression equipment is adjusted in time to ensure that efficient dust control can be achieved in different environments.

[0141] The automated dust suppression control method based on environmental data also incorporates other intelligent analysis technologies. The examples leverage advanced technologies such as big data and artificial intelligence to mine, analyze, and integrate spray particle size analysis results, spray length predictions, spray velocity calculations, and environmental target monitoring information. A database is then established to store and manage historical data, providing data resources for subsequent environmental data analysis and model training.

[0142] Based on machine learning algorithms and historical data, the spray particle size analysis function, injection length prediction function and injection velocity calculation function in the control instruction reference system are learned and trained, so that the relevant function model can accurately predict the control instruction reference indicators under different parameters, and provide a decision-making basis for the adjustment and control of automated dust suppression equipment.

[0143] At the same time, an intelligent decision-making module is introduced to integrate the analysis results of various functions and monitoring information. The intelligent decision-making module can automatically generate optimal control instructions for different environments based on real-time data, preset rules for different environments, and environmental dust detection conditions, and adjust the operating status of the automated dust suppression equipment in real time. In an optional embodiment, when a sudden increase in dust concentration in the treatment area is detected, the intelligent decision-making system can quickly analyze the cause and automatically adjust the operating parameters of the system dust suppression equipment according to the preset emergency plan, including but not limited to increasing the spray volume and injection frequency, to quickly reduce the dust concentration in the environment.

[0144] In addition, the automated dust suppression control method based on environmental data also includes the establishment of a data visualization platform to display information such as control instruction reference indicators, environmental monitoring data, and equipment operating status in the form of intuitive charts and graphs. Through the data visualization platform, the dust pollution status of the treatment area and the operation status of the system dust suppression equipment can be understood in real time, problems can be discovered and solved in a timely manner, and the efficiency and effectiveness of dust control can be improved.

[0145] See Figure 2 In an optional embodiment, in order to efficiently execute the automated dust suppression control method based on environmental data provided by the present invention, the present invention further provides an automated dust suppression control system based on environmental data, the system comprising a processor, an input device, an output device, and a memory, wherein the processor, input device, output device, and memory are interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to call the program instructions to execute the specific steps of the automated dust suppression control method based on environmental data provided by the present invention and related embodiments. The automated dust suppression control system based on environmental data of the present invention is structurally complete, objective, and stable.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. An automated dust suppression control method based on environmental data, characterized in that: The method comprises: Use the environmental information monitoring and transmission module to obtain the initial environmental detection data of the area to be treated; Analyzing the wind speed conditions in the area to be treated based on the initial environmental detection data, establishing an environmental dust concentration correction model based on the wind speed conditions, and obtaining environmental target monitoring information for the area to be treated based on the environmental dust concentration correction model and the initial environmental detection data; Setting a control instruction reference system in the automated dust suppression equipment, and obtaining a control reference index analysis result of the automated dust suppression equipment based on the environmental target monitoring information and the control instruction reference system; Based on the control reference index analysis results and the environmental target monitoring information, the automated dust suppression equipment in the treatment area is adjusted and controlled to achieve effective dust control in the treatment area.

2. The automatic dust suppression control method based on environmental data according to claim 1 is characterized in that: Analyzing the wind speed of the area to be processed based on the initial environmental detection data includes: Establishing an environmental wind speed prediction function for the area to be processed based on air movement characteristics and the initial environmental detection data; Analyze the environmental wind speed results corresponding to different times in the area to be processed by the environmental wind speed prediction function; The wind speed condition of the area to be processed is analyzed by combining the environmental wind speed result and the environmental initial detection data.

3. The automatic dust suppression control method based on environmental data according to claim 2, characterized in that: The step of establishing an environmental wind speed prediction function for the area to be processed based on the air movement characteristics and the initial environmental detection data includes: The ambient wind speed prediction function satisfies the following relationship: ， in, express The wind speed corresponding to the center of the processing area at a time point, Indicates the highest detection height of the processing area, Indicates the lowest detection height of the processing area, represents the wind shear index corresponding to the center of the processing area, represents the aerodynamic roughness, express exist The wind speed value corresponding to the time point, express exist The wind speed value corresponding to the time point.

4. The automatic dust suppression control method based on environmental data according to claim 2, characterized in that: The step of establishing an environmental dust concentration correction model according to the wind speed conditions and obtaining environmental target monitoring information of the area to be processed based on the environmental dust concentration correction model and the initial environmental detection data includes: Establishing an environmental dust concentration correction model based on the dust diffusion law and the wind speed conditions; Obtaining dust concentration detection information at different time points in the area to be treated based on the initial environmental detection data; The dust concentration detection information is processed using the environmental dust concentration correction model to obtain environmental target monitoring information of the area to be processed.

5. The automatic dust suppression control method based on environmental data according to claim 4 is characterized in that: The establishment of an ambient dust concentration correction model based on the dust diffusion law and the wind speed conditions includes: The ambient dust concentration correction model satisfies the following relationship: ， in, Indicates the processing area Dust concentration at a given time point, express The original dust concentration in the treatment area at a given time point, express The corresponding motion characteristic parameters, Indicates the geometric eigenvalue corresponding to the processing area, express Air flow in the treatment area at a given time point, express Parameter value corresponding to the average temperature of the processing area at a time point.

6. The automatic dust suppression control method based on environmental data according to claim 1, characterized in that: The control instruction reference system for setting up the automatic dust suppression equipment includes: Selecting control instruction reference indicators for the automated dust suppression equipment based on the working principle of the automated dust suppression equipment and the environmental target monitoring information, wherein the control instruction reference indicators include the spray particle size, spray length, and spray speed of the automated dust suppression equipment; A control instruction reference system for automated dust suppression equipment is constructed based on the spray particle size, the injection length, and the injection speed.

7. The automatic dust suppression control method based on environmental data according to claim 6, characterized in that: The control reference index analysis results of the automated dust suppression equipment obtained based on the environmental target monitoring information and the control instruction reference system include: Establishing a spray particle size analysis function, a spray length prediction function, and a spray velocity calculation function in the control instruction reference system; The control reference index analysis results of the automatic dust suppression equipment are obtained through the spray particle size analysis function, the injection length prediction function and the injection speed calculation function.

8. The automatic dust suppression control method based on environmental data according to claim 7, characterized in that: The establishment of a spray particle size analysis function, a spray length prediction function and a spray velocity calculation function in the control instruction reference system includes: The spray particle size analysis function satisfies the following relationship: ， in, Indicates the droplet size of dust suppression equipment at different times, Indicates the processing area Dust concentration at a given time point, express The air velocity corresponding to the center of the processing area at a time point, express The wind speed corresponding to the center of the processing area at a time point, express Average dust particle size in the treatment area at a given time point, represents the constant term in the particle size analysis function, represents the dynamic viscosity of air, represents the inertial collision coefficient; The injection length prediction function satisfies the following relationship: ， in, Indicates the range of dust suppression equipment at different times, represents the first fitting coefficient of the jet length prediction function, represents the second fitting coefficient of the jet length prediction function, represents the third fitting coefficient of the jet length prediction function, represents the ratio of the ejecta inertial force to the viscous force, Indicates the tension coefficient corresponding to the droplet size of dust suppression equipment at different times, Indicates the nozzle radius of the dust suppression equipment; The injection velocity calculation function satisfies the following relationship: ， in, Indicates the average injection velocity of dust suppression equipment at different times, Indicates the initial injection velocity of dust suppression equipment at different times, represents the air density, Indicates the drag coefficient value, Indicates the droplet density of dust suppression equipment at different times, Indicates the average droplet size of dust suppression equipment at different times.

9. The automatic dust suppression control method based on environmental data according to claim 8, characterized in that: The adjusting and controlling of the automated dust suppression equipment in the treatment area based on the control reference index analysis results and the environmental target monitoring information to achieve effective dust control in the treatment area includes: The control instruction reference index of the automatic dust suppression equipment is adjusted and controlled in combination with the spray particle size analysis results, the injection length prediction results, the injection velocity calculation results and the environmental target monitoring information to achieve effective control of dust in the processing area.

10. The automatic dust suppression control system based on environmental data is characterized by: The system includes a processor, an input device, an output device and a memory, which are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the automated dust suppression control method based on environmental data as described in any one of claims 1 to 9.

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